Recommender system, Learning, Machine learning, Cold start, Language model, Implicit data collection

The Best of RecSys 2020

On Sep 29, 2020
@xamat shared
RT @urinieto: I selected my favorite content of #recsys2020. As a first timer, I really enjoyed this conference! I just missed the real caipirinhas https://t.co/JL1rvvd1yB
Open

PhD in Music Data Science

urinieto.com
On Sep 29, 2020
@xamat shared
RT @urinieto: I selected my favorite content of #recsys2020. As a first timer, I really enjoyed this conference! I just missed the real caipirinhas https://t.co/JL1rvvd1yB
Open

The Best of RecSys 2020

The Best of RecSys 2020

PhD in Music Data Science

Recommendation Systems in the Real World

Recommendation Systems in the Real World

Too few choices are bad but too many choices can lead to paralysis Have you heard about the famous Jam Experiment? In 2000, psychologists Sheena Iyengar and Mark Lepper from Columbia and ...

Announcing NVIDIA Merlin: An Application Framework for Deep Recommender Systems

Announcing NVIDIA Merlin: An Application Framework for Deep Recommender Systems

Recommender systems drive every action that you take online, from the selection of this web page that you’re reading now to more obvious examples like online shopping. They play a critical ...

How Netflix uses AI to Predict Your Next Series Binge - 2020

How Netflix uses AI to Predict Your Next Series Binge - 2020

How Netflix uses AI to Predict Your Next Series Binge? We asked the experts.

What have been the greatest AI advances of 2019?

What have been the greatest AI advances of 2019?

The revolution may get unsupervised at some point, but for now we can make it self-supervised Computers continue to get better at playing games and can now collaborate in multi-agent ...

The year in AI: 2019 ML/AI advances recap

The year in AI: 2019 ML/AI advances recap

It has become somewhat of a tradition for me to do an end-of-year retrospective of advances in AI/ML (see last year’s round up for…

Xavier Amatriain’s Machine Learning and Artificial Intelligence 2019 Year-end Roundup

Xavier Amatriain’s Machine Learning and Artificial Intelligence 2019 Year-end Roundup

It is an annual tradition for Xavier Amatriain to write a year-end retrospective of advances in AI/ML, and this year is no different. Gain an understanding of the important developments of ...

New Graphcore IPU benchmarks

New Graphcore IPU benchmarks

New Graphcore IPU benchmarks for training and inference machine learning models

The Great AI Bake-Off: Recommendation Systems on the Rise

The Great AI Bake-Off: Recommendation Systems on the Rise

Winners of an annual competition share their secrets for using machine learning to personalize consumer services.

Accepted Contributions

Accepted Contributions

LPEnhancing Structural Diversity in Social Networks by Recommending Weak Ties by Javier Sanz-Cruzado, Pablo Castells Contact recommendation has become a common functionality in online ...

How you can use the same powerful machine learning Netflix uses

How you can use the same powerful machine learning Netflix uses

Did you ever wonder why the artwork Netflix uses for different shows sometimes changes when you login to your account day-to-day? One day…

Health Checks for Machine Learning - A Guide to Model Retraining and Evaluation

Health Checks for Machine Learning - A Guide to Model Retraining and Evaluation

Machine Learning in production is exponentially more difficult than offline experiments. In this blog we talk about model evaluation, maintenance and retraining.

Applying Deep Learning To Airbnb Search

Applying Deep Learning To Airbnb Search

Lambdarank gave us a way to directly optimize def apply_discount(x): '''Apply positional discount curve''' return np.log(2.0)/np.log(2.0 + x) def compute_weights(logit_op, session): ...